Titanic - Machine Learning from DisasterStart here! Predict survival on the Titanic and get familiar with ML basics
人間参加型（human-in-the-loop）機械学習とは？
We help companies test and improve machine learning models via our global AI Community of 1 million+ annotators and linguists. Our proprietary Ground Truth AI training platform handles all data types across 500+ languages and dialects. Our AI Data Solutions vastly enhance AI systems across a range of applications from advanced smart products, to better search results, to expanded speech recognitio
UCI Machine Learning Repository
Predict whether annual income of an individual exceeds $50K/yr based on census data. Also known as "Census Income" dataset.
統計、機械学習の勉強で使いやすい生データをダウンロードできるリンク集 - Qiita
はじめに 統計、機械学習が流行しているので、勉強したいと考えている人が多いと思います。 が、しかし、実際に手を動かすためには、データがないと難しく勉強は困難です。 PRMLとか読んでも、実務で使えそうなイメージは湧きません。 そこで、生データをダウンロードできるリンク集を作ってみました。 見つけ次第増やしていきます。 過去の気象データ検索 by 気象庁 http://www.data.jma.go.jp/obd/stats/etrn/index.php 気象に関する情報のデータベースです。 条件を色々入れると、CSVを生成してくれます。 データ容量制限がありますが、いろいろ使えそうです。 人体寸法データベース by 産総研 https://www.dh.aist.go.jp/database/91-92/ 身体のいろんな場所の寸法に関するデータベースです。 足のサイズとか、顔の大きさとかの
UCI Machine Learning Repository: Beijing PM2.5 Data Data Set
Source: Song Xi Chen, csx '@' gsm.pku.edu.cn, Guanghua School of Management, Center for Statistical Science, Peking University. Data Set Information: The data’s time period is between Jan 1st, 2010 to Dec 31st, 2014. Missing data are denoted as “NA�. Attribute Information: No: row number year: year of data in this row month: month of data in this row day: day of data in this row hour: hour o
UCI Machine Learning Repository
All atrributes are numeric and continuous N. Attrib. 1 Q-E (input flow to plant) 2 ZN-E (input Zinc to plant) 3 PH-E (input pH to plant) 4 DBO-E (input Biological demand of oxygen to plant) 5 DQO-E (input chemical demand of oxygen to plant) 6 SS-E (input suspended solids to plant) 7 SSV-E (input volatile supended solids to plant) 8 SED-E (input sediments to plant) 9 COND-E (input conductivity to p
UCI Machine Learning Repository: Reuters-21578 Text Categorization Collection Data Set
Source: David D. Lewis AT&T Labs - Research lewis '@' research.att.com Documents came from Reuters newswire in 1987. Data Set Information: From the original readme file (please consult it for more information): ------------------------- The documents in the Reuters-21578 collection appeared on the Reuters newswire in 1987. The documents were assembled and indexed with categories by personnel from
UCI Machine Learning Repository
Data was used to test 2 tier approach with learning from positive and negative examples 1. dur: duration of agreement [1..7] 2 wage1.wage : wage increase in first year of contract [2.0 .. 7.0] 3 wage2.wage : wage increase in second year of contract [2.0 .. 7.0] 4 wage3.wage : wage increase in third year of contract [2.0 .. 7.0] 5 cola : cost of living allowance [none, tcf, tc] 6 hours.hrs : number
UCI Machine Learning Repository: Auto MPG Data Set
This dataset is a slightly modified version of the dataset provided in the StatLib library. In line with the use by Ross Quinlan (1993) in predicting the attribute "mpg", 8 of the original instances were removed because they had unknown values for the "mpg" attribute. The original dataset is available in the file "auto-mpg.data-original". "The data concerns city-cycle fuel consumption in miles per
UCI Machine Learning Repository
The PAMAP2 Physical Activity Monitoring dataset contains data of 18 different physical activities (such as walking, cycling, playing soccer, etc.), performed by 9 subjects wearing 3 inertial measurement units and a heart rate monitor. The dataset can be used for activity recognition and intensity estimation, while developing and applying algorithms of data processing, segmentation, feature extract
UCI Machine Learning Repository
Bike sharing systems are new generation of traditional bike rentals where whole process from membership, rental and return back has become automatic. Through these systems, user is able to easily rent a bike from a particular position and return back at another position. Currently, there are about over 500 bike-sharing programs around the world which is composed of over 500 thousands bicycles. Tod
UCI Machine Learning Repository
1) S1 "Suit of card #1" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 2) C1 "Rank of card #1" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 3) S2 "Suit of card #2" Ordinal (1-4) representing {Hearts, Spades, Diamonds, Clubs} 4) C2 "Rank of card #2" Numerical (1-13) representing (Ace, 2, 3, ... , Queen, King) 5) S3 "Suit of card #3" Ordinal (1-4) representing {Hearts,
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UCI Machine Learning Repository
Features are computed from a digitized image of a fine needle aspirate (FNA) of a breast mass. They describe characteristics of the cell nuclei present in the image. A few of the images can be found at http://www.cs.wisc.edu/~street/images/ Separating plane described above was obtained using Multisurface Method-Tree (MSM-T) [K. P. Bennett, "Decision Tree Construction Via Linear Programming." Proce
UCI Machine Learning Repository
This is one of the earliest datasets used in the literature on classification methods and widely used in statistics and machine learning. The data set contains 3 classes of 50 instances each, where each class refers to a type of iris plant. One class is linearly separable from the other 2; the latter are not linearly separable from each other. Predicted attribute: class of iris plant. This is an e
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https://dl.acm.org/doi/10.1145/2827872
UCI Machine Learning Repository
https://archive.ics.uci.edu/ml/machine-learning-databases/iris/iris.data
https://archive.ics.uci.edu/ml/machine-learning-databases/breast-cancer-wisconsin/wdbc.data
UCI Machine Learning Repository
Index of /ml/machine-learning-databases/covtype